Stockpyl

Stockpyl suits analysts and developers who want to build inventory models in Python, from single-node decisions to multi-echelon systems. Its strongest case is a focused, MIT-licensed toolkit with both optimization and simulation; its trade-off is a technical workflow rather than a ready-made business application.

Overview

Stockpyl brings several established inventory approaches into one Python package: economic order quantity, newsvendor, and Wagner-Whitin models, plus multi-echelon optimization and simulation. That range makes it useful for comparing model types without switching tools, particularly in education, business analysis, or scientific and engineering work.

Installation is through PyPI using pip install stockpyl, and requires Python v3.7 or later. The MIT License permits open-source use. Tutorials and API documentation cover optimization, simulation, and supply-chain data structures. For problems or feedback, the project points users to GitHub Issues, with email as another route; this suits users able to work through a software-project support channel.

Key features

Single-node and multi-echelon models

Alongside economic order quantity, newsvendor, and Wagner-Whitin methods, Stockpyl includes multi-echelon optimization for stochastic-service and guaranteed-service models. Safety stock optimization is supported as well. The breadth is valuable when the work calls for comparing inventory formulations, but users need to be comfortable expressing that work through a Python package.

Optimization and simulation

Documented methods include dynamic programming for Wagner-Whitin and finite-horizon stochastic inventory problems. The package also simulates multi-echelon inventory systems, giving analysts both optimization methods and a way to examine system behavior in simulation. Its network algorithms cover serial systems and acyclical guaranteed-service systems, making those structures a particular fit rather than implying support for every possible network design.

Pricing

Stockpyl is free: the Stockpyl plan costs free and is an open-source Python package under the MIT License. There is no paid tier to trade features against, so the main cost is working within the Python environment and the models the package provides. The project does not state seat or usage quotas.

Platforms

Stockpyl is listed for API and Linux use. It installs with pip and requires Python v3.7 or later, so it is best suited to Linux or API workflows where Python is already part of the environment, not readers looking for a conventional desktop inventory interface.

Who it's for

Choose Stockpyl if you are an analyst, developer, student, or researcher who wants inventory optimization and simulation methods inside Python, and values an open-source MIT-licensed package. Look elsewhere if your priority is a packaged business tool with a non-technical user workflow or commercial support.

Pros and cons

• Pros: Covers EOQ, newsvendor, Wagner-Whitin, and several multi-echelon methods, useful for comparing inventory models in one package.
• Pros: Combines optimization with multi-echelon simulation, supporting both model-solving and system-behavior analysis.
• Pros: Free and MIT-licensed, with tutorials and API documentation for the core modules.
• Cons: Requires Python v3.7 or later and a Python-oriented workflow, which rules it out for users seeking a turnkey business application.
• Cons: Support is routed through GitHub Issues or email rather than a stated dedicated commercial support service.

Alternatives

Inventory Optimization Software is the broader category to browse if you want to compare tools beyond a Python package.

ZebraDesigner is a paid option with a free plan and free trial, and is a better match when barcode label and tag design and printing for Zebra Link-OS printers are the priority.

Creo is a paid design product with floating licensing, so consider it when organizational users need a shared concurrent license rather than inventory modeling in Python.

Manhattan Active Inventory Replenishment is a paid alternative for readers looking for an inventory replenishment product rather than an open-source Python package.

Bluemingo Production Planning & Scheduling has custom pricing and is an option to consider when production planning and scheduling is the focus.

E2open Planning has custom pricing; consider it as another paid planning alternative.

GAINS has custom pricing and is another paid option for readers comparing inventory software.

Logility DemandAI+ has custom pricing and is another paid planning alternative.

4R Systems Intelligent Inventory Optimization has custom pricing and is another paid option to compare for inventory optimization.

Verdict

Stockpyl is a strong choice for Python-comfortable analysts and developers who need established inventory optimization methods plus multi-echelon simulation without a license fee. Its technical workflow is also the decisive reason to look elsewhere: users who need a conventional business application should compare commercial inventory tools instead.